SeBS: A Serverless Benchmark Suite for Function-as-a-Service Computing
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Abstract (arXiv)
Function-as-a-Service (FaaS) is one of the most promising directions for the future of cloud services, and serverless functions have immediately become a new middleware for building scalable and cost-efficient microservices and applications. However, the quickly moving technology hinders reproducibility, and the lack of a standardized benchmarking suite leads to ad-hoc solutions and microbenchmarks being used in serverless research, further complicating metaanalysis and comparison of research solutions. To address this challenge, we propose the Serverless Benchmark Suite: the first benchmark for FaaS computing that systematically covers a wide spectrum of cloud resources and applications. Our benchmark consists of the specification of representative workloads, the accompanying implementation and evaluation infrastructure, and the evaluation methodology that facilitates reproducibility and enables interpretability. We demonstrate that the abstract model of a FaaS execution environment ensures the applicability of our benchmark to multiple commercial providers such as AWS, Azure, and Google Cloud. Our work facilities experimental evaluation of serverless systems, and delivers a standardized, reliable and evolving evaluation methodology of performance, efficiency, scalability and reliability of middleware FaaS platforms.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Dec 2020.
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Citing papers per year: 2021: 4; 2022: 2; 2023: 0; 2024: 4; 2025: 0; 2026: 1.
11 papers.
- 2024Demystifying Chains, Trees, and Graphs of Thoughtscited by 63
- 2022Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency Analysiscited by 29
- 2021Motif Prediction with Graph Neural Networkscited by 18
- 2022Neural Graph Databasescited by 11
- 2021GraphMineSuite: Enabling High-Performance and Programmable Graph Mining Algorithms with Set Algebracited by 10
- 2024Demystifying Higher-Order Graph Neural Networkscited by 4
- 2021Serverless Data Science -- Are We There Yet? A Case Study of Model Servingcited by 3
- 2021Accelerating Serverless Computing by Harvesting Idle Resourcescited by 0
- 2024Shabari: Delayed Decision-Making for Faster and Efficient Serverless Functionscited by 0
- 2024Input-Based Ensemble-Learning Method for Dynamic Memory Configuration of Serverless Computing Functionscited by 0
- 2026High-Performance Serverless Computing: A Systematic Literature Review on Serverless for HPC, AI, and Big Datacited by 0
- 2026High-Performance Serverless Computing: A Systematic Literature Review on Serverless for HPC, AI, and Big Data14 Jan 2026
- 2024Input-Based Ensemble-Learning Method for Dynamic Memory Configuration of Serverless Computing Functions12 Nov 2024
- 2024Demystifying Higher-Order Graph Neural Networks18 Jun 2024
- 2024Demystifying Chains, Trees, and Graphs of Thoughts25 Jan 2024
- 2024Shabari: Delayed Decision-Making for Faster and Efficient Serverless Functions16 Jan 2024
- 2022Neural Graph Databases20 Sep 2022
- 2022Parallel and Distributed Graph Neural Networks: An In-Depth Concurrency Analysis19 May 2022
- 2021Accelerating Serverless Computing by Harvesting Idle Resources28 Aug 2021
- 2021Motif Prediction with Graph Neural Networks26 May 2021
- 2021GraphMineSuite: Enabling High-Performance and Programmable Graph Mining Algorithms with Set Algebra5 Mar 2021
- 2021Serverless Data Science -- Are We There Yet? A Case Study of Model Serving4 Mar 2021